Stability and Hopf Bifurcation Analysis of a Phytoplankton-Zooplankton Model Under Temperature Factor and Stage-Structure Population of Phytoplankton

Nguyen Phuong Thuy1,, Cao Thi Phuong1, Van Duc An1, Nguyen Duc Anh1
1 Hanoi University of Science and Technology, Ha Noi, Vietnam

Main Article Content

Abstract

In the paper, we built a predator-prey model to simulate and study the dynamics of zooplankton and phytoplankton populations under the temperature impact, in which the stage structure is considered in the zooplankton population. Our model is an ordinary differential system of three nonlinear equations with some parameters as temperature-dependent functions and uses the generalized Holling response function. The non-negative and boundedness of the model solutions have been proven. The behaviors of our system are shown by the local stability conditions of the equilibria, especially the co-existence case. The stage transformation of zooplankton was studied through the Hopf bifurcation results of varying the temperature.
The analysis and simulation results indicate that the ideal temperature for the co-existence is about 12-21 degrees Celsius. The zooplankton's transformation decreases when the temperature increases, leading to an imbalance in the system. Besides that, we also provided simulation figures to illustrate the found theoretical results.

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References

[1] B. C. Rall, O. Vucic-pestic, R. B. Ehnes, M. Emmerson and U. Brose, Temperature, predator-prey interaction strength and population stability, Global Change Biology, 16, 2010, 2145- 2157. https://doi.org/10.1111/j.1365-2486.2009.02124.x
[2] J. L. Lessard and D. B. Hayes, Effects of elevated water temperature on fish and macroinvertebrate communities below small dams, River Research and Applications, 19, 2003, 721-732. https://doi.org/10.1002/rra.713
[3] J. C. Morrill, R. C. Bales and M. H. Conklin, Estimating stream temperature from air temperature: implications for future water quality, Journal of Environmental Engineering, 131, 2005, 139-146. https://doi.org/10.1061/(ASCE)0733- 9372(2005)131:1(139)
[4] L. S. Peck, K. E. Webb and D. M. Bailey, Extreme sensitivity of biological function to temperature in antarctic marine species, Functional Ecology, 18, 2004, 625-630. https://doi.org/10.1111/j.0269-8463.2004.00903.x
[5] P. A. Staehr and K. A. J. Sand-Jensen, Seasonal changes in temperature and nutrient control of photosynthesis, respiration and growth of natural phytoplankton communities, Freshwater Biology, 51, 2. 2006, 249-262. https://doi.org/10.1111/j.1365-2427.2005.01490.x
[6] A. Toseland, S. J. Daines, J. R. Clark, A. Kirkham, J. Strauss, C. Uhlig, T. M. Lenton, K. Valentin, G. A. Pearson, V. Moulton and T. Mock, The impact of temperature on marine phytoplankton resource allocation and metabolism, Nature Climate Change, 3, 2013. https://doi.org/10.1038/nclimate1989
[7] K. E. Havens, R .M Ointo-Coelho, M. Beklioglu, K. S. Christoffersen, E.Jeppesen, T. Lauridsen, A. Mazumder, G. Methot, B .P. Alloul, U. N. Tavsanoglu, S. Erdogan and J. Vijverberg, Temperature effects on body size of freshwater crustacean zooplankton from greenland to the tropics, Hydrobiologia 743, 2015, 27-35. https://doi.org/10.1007/s10750-014-2000-8
[8] J. G. Choi, T. C. Lippmann and E. L. Harvey, Analytical population dynamics underlying harmful algal blooms triggered by prey avoidance, Ecological Modelling, 481, 2023, 110366. https://doi.org/10.1016/j.ecolmodel.2023.110366
[9] A. Gera, R. Gayathri, P. Ezhilarasan, V. R. Rao and M.V.R Murthy, Coupled physical-biogeochemical simulations of upwelling, ecological response to fresh water, Ecological Modelling, 476, 2023, 110246. https://doi.org/10.1016/j.ecolmodel.2022.110246
[10] T. Chu, H. V. Moeller and K. M. Archibald, Competition between phytoplankton and mixotrophs leads to metabolic character displacement, Ecological Modelling, 481, 2023, 110331. https://doi.org/10.1016/j.ecolmodel.2023.110331
[11] A. Mandal, P. K. Tiwari and S. Pal, A nonautonomous model for the effects of refuge and additional food on the dynamics of phytoplankton-zooplankton system, Ecological Complexity, 46, 2021, 100927. https://doi.org/10.1016/j.ecocom.2021.100927
[12] K. Agnihotri and H. Kaur, Optimal control of harvesting effort in a phytoplankton-zooplankton model with infected zooplankton under the influence of toxicity, Mathematics and Computers in Simulation, 190, 2021, 946-964. https://doi.org/10.1016/j.matcom.2021.06.022
[13] S. N. Raw and S. R. Sahu, Strong stability with impact of maturation delay and diffusion on a toxin producing phytoplankton-zooplankton model, Mathematics and Computers in Simulation, 210, 2023, 547-570. https://doi.org/10.1016/j.matcom.2023.03.023
[14] Q. Zhao, S. Liu and X. Niu, Effect of water temperature on the dynamic behavior of phytoplankton - zooplankton model, Applied Mathematics and Computation, 378, 2020, 125211. https://doi.org/10.1016/j.amc.2020.125211
[15] J. M. Jackson and P. H. Lenz, Predator-prey interactions in the plankton: larval fish feeding on evasive copepods, Sci Rep 6, 33585, 2016. https://doi.org/10.1038/srep33585
[16] I. Mclaren, Effects of temperature on growth of zooplankton, and the adaptive value of vertical migration, Journal of the Fisheries Research Board of Canada, 20, 2011, 685-727. https://doi.org/10.1139/f63-046
[17] W. Uszko, S. Diehl, G. Englund and P. Amarasekare, Effects of warming on predator- prey interactions - a resource-based approach and a theoretical synthesis, Ecology Letters, 20, 2017, 513-523. https://doi.org/10.1111/ele.12755